The research aims to combine the efficiencies of SDNs with new reinforcement learning, cognitive algorithms and enhanced protocols to automatize SDN systems and to leverage self-healing (SH) paradigm as an approach for improving the SDN robustness and predictability. The research is based on autonomic network management and control concepts, providing the network with the capability of local self-adaptation. The objective is to dynamically minimize communication overhead associated with network state information and traffic statistics required by the controller, characterizing the traffic behaviour in order to accurate performance evaluation and predication.

• Design and analysis of a framework for the Path Computing under QoX Constraints using NFV Functions

Network function virtualization (NFV) and software-defined networking (SDN) represent new paradigms in networking, to be deployed in the coming networks, exploiting the features provided by SDN to introduce QoX and to use NFV in order to perform the necessary tasks to calculate optimal paths.

Hence, this PhD thesis aims to propose and analyze the behavior of a novel path computing framework under QoX constraints based on NFV functions.

Specific works to be done:

- Definition of procedures to select the optimal paths. Definition of problem. Formulation of problem. Evaluation and heuristics regarding NP-hardness.

- Definition of metrics.

- Assessment.

- Definition of use cases. Application of the results to the cloud, Smart networks, data centers and IoT.

One of the main challenges in network virtualization is the virtual network embedding problem (VNE). The objective of the VNE is to map a set of Virtual Network Requests (VNR) to physical nodes and links. VNR is composed by a set of virtual nodes and links with several demands (traditionally CPU and bandwidth) to be assigned into a set of paths in the substrate network with sufficient resources. Embedding can be optimized with regard to specific metrics. To help solving the VNE problem a mathematical tool has been proposed, called Paths Algebra, to deal with the VNE multi-constraint problem using linear metrics. Most of the existing VNE proposals treat the single-path virtual link-mapping problem as a mono-constraint. This PhD thesis is focused in the study, analysis and validation of the mathematical framework of Path Algebra under selected linear (CPU, bandwidth and energy consumption) and non-linear metrics (availability and packet loss ratio), providing performance results, in 2 scenarios: Off-line and On-line.

5G will provide an ultra-broadband and low latency wired and wireless communications centred on the end user.

This work is addressed to design and implement a new open optical access network architecture, that based on SDN and NFV principles, control and manages an ultra-broad band optical access network, working both legacy such new optical transport schemes. The architecture elements will be open and flexible integrating the existing PON technologies.

Their adaptive mechanisms will fuse the optical backbone data plane with the 5G optical access networks providing a seamless communication infrastructure offering service on demand

The backhaul networks for the upcoming 5th generation (5G) cellular systems will need to transport a relatively large amount of data with high flexibility requirements. Also, we can expect stringent conditions for the backhaul network to be met, in the same way that it is true for Long-Term Evolution (LTE) and LTE-A (LTE-Advanced) cellular systems at present. The heterogeneity of 5G also poses new challenges and opportunities for the backhaul network design. In this context, the PhD research project is dedicated to the development of novel backhaul networks for 5G, including multi-technology solutions (either using optical fibre or wireless links) and advanced topological innovations. Also, given the expected heterogeneity of the 5G cellular system, the work will consider the incorporation of the Software Defined Networking paradigm to the backhaul network control as a powerful strategy to meet these challenges.

According to several studies, the power consumption of the Internet accounts for up to 10% of the worldwide energy consumption, and there are opinions that this energy consumption can only grow as the Internet expands and the use of streaming applications and video over demand increased. Several initiatives have appeared to reduce this power consumption.

The objective of this work is to develop mechanism that use the options that the hardware offers to control the power consumption as putting some or all components of the device into low-energy sleep state or clocking the hardware slower (Dynamic Voltage Scaling - DVS) and the knowledge that the SDN architecture offers of the network. So there is the possibility of using Traffic Engineering for finding routes that permits to put the maximum number of components in sleep state of assignment of resources to Virtual Function Networks to optimize the power consumption.

Applicants must fulfil the normal academic requirements for postgraduate study. M.Sc. or equivalent in Computer Science, Electrical Engineering, Computer Engineering, Telecommunications, Telematics or a related field. Besides for each proposal there are specific requirements.

Financial aid:

There is an open call opportunity to get financial support through the scholarships that offers Obra Social "la Caixa" for Ph. D. studies in Spain (they are only for Spanish citizens), you can get more information in the following links: